phoenix vs helicone
LLM observability and application tooling compared
phoenix and helicone both help teams inspect and improve LLM applications. phoenix emphasizes OpenTelemetry-based tracing, evaluation, and experimentation, while helicone combines observability with a gateway for routing requests across model providers.
phoenix: Observe and Evaluate AI Applications
Arize Phoenix is a self-hosted platform for tracing, evaluating, and troubleshooting LLM applications. It helps AI engineers inspect runtime behavior and test changes to prompts, models, and retrieval.
helicone: Monitor and Route LLM Requests
Helicone is a TypeScript platform for observing LLM requests and routing them across model providers. It helps AI teams inspect traces, track cost and latency, manage prompts, and self-host the observability stack.
| phoenix | helicone | |
|---|---|---|
| Language | Python | TypeScript |
| License | NOASSERTION | Apache-2.0 |
| Stars | 11.7k | 6.2k |
| Forks | 1.2k | 683 |
| Last analyzed | Oct 3, 2026 | Oct 7, 2026 |
Key differences
- phoenix centers on application traces, datasets, evaluations, and experiments; helicone adds a unified API gateway with routing and automatic fallbacks.
- phoenix supports self-hosting on a local machine, in containers, or in the cloud; helicone's self-hosting path uses multiple services and recommends Docker or Helm.
- phoenix is written in Python and helicone in TypeScript.
- phoenix's repository metadata lists its license as NOASSERTION, while its README describes Elastic License 2.0; helicone lists Apache-2.0.
- phoenix integrates through OpenTelemetry and OpenInference instrumentation; helicone offers an OpenAI-compatible gateway and integrations with tools such as LangChain, LlamaIndex, and the Vercel AI SDK.
- The supplied repository data lists phoenix at 11.7k stars and 1.2k forks, and helicone at 6.2k stars and 680 forks.
Choose phoenix if you…
- need tracing and evaluation across LLM calls, retrieval, and agent workflows.
- want to build datasets and compare prompt, model, or retrieval changes through experiments.
- prefer a self-hosted observability platform with options including local and container deployment.
Choose helicone if you…
- need a gateway to route requests across model providers and configure fallbacks.
- want to track request cost and latency alongside traces and sessions.
- need prompt version management and a Docker- or Helm-based self-hosting option.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.